ABSTRACT
Despite traditionally regarded as identical, cells in a microbial cultivation present a distribution of phenotypic traits, forming a heterogeneous cell population. Moreover, the degree of heterogeneity is notably enhanced by changes in micro-environmental conditions. A major development in experimental single-cell studies has taken place in the last decades. It has however not been fully accompanied by similar contributions within data analysis and mathematical modeling. Indeed, literature reporting, for example, quantitative analyses of experimental single-cell observations and validation of model predictions for cell property distributions against experimental data is scarce. This study focuses on the experimental and mathematical description of the dynamics of cell size and cell cycle position distributions, of a population of Saccharomyces cerevisiae, in response to the substrate consumption observed during batch cultivation. The good agreement between the proposed multi-scale model (a population balance model [PBM] coupled to an unstructured model) and experimental data (both the overall physiology and cell size and cell cycle distributions) indicates that a mechanistic model is a suitable tool for describing the microbial population dynamics in a bioreactor. This study therefore contributes towards the understanding of the development of heterogeneous populations during microbial cultivations. More generally, it consists of a step towards a paradigm change in the study and description of cell cultivations, where average cell behaviors observed experimentally now are interpreted as a potential joint result of various co-existing single-cell behaviors, rather than a unique response common to all cells in the cultivation.
Subject(s)
Cell Cycle , Saccharomyces cerevisiae/physiology , Cell Size , Flow Cytometry , Models, Theoretical , Saccharomyces cerevisiae/cytology , Saccharomyces cerevisiae/growth & developmentABSTRACT
The cyanobacterium Acaryochloris marina is the only known phototroph harboring chlorophyll (Chl) d. It is easy to cultivate it in a planktonic growth mode, and A. marina cultures have been subject to detailed biochemical and biophysical characterization. In natural situations, A. marina is mainly found associated with surfaces, but this growth mode has not been studied yet. Here, we show that the A. marina type strain MBIC11017 inoculated into alginate beads forms dense biofilm-like cell clusters, as in natural A. marina biofilms, characterized by strong O(2) concentration gradients that change with irradiance. Biofilm growth under both visible radiation (VIS, 400 to 700 nm) and near-infrared radiation (NIR, â¼700 to 730 nm) yielded maximal cell-specific growth rates of 0.38 per day and 0.64 per day, respectively. The population doubling times were 1.09 and 1.82 days for NIR and visible light, respectively. The photosynthesis versus irradiance curves showed saturation at a photon irradiance of E(k) (saturating irradiance) >250 µmol photons m(-2) s(-1) for blue light but no clear saturation at 365 µmol photons m(-2) s(-1) for NIR. The maximal gross photosynthesis rates in the aggregates were â¼1,272 µmol O(2) mg Chl d(-1) h(-1) (NIR) and â¼1,128 µmol O(2) mg Chl d(-1) h(-1) (VIS). The photosynthetic efficiency (α) values were higher in NIR-irradiated cells [(268 ± 0.29) × 10(-6) m(2) mg Chl d(-1) (mean ± standard deviation)] than under blue light [(231 ± 0.22) × 10(-6) m(2) mg Chl d(-1)]. A. marina is well adapted to a biofilm growth mode under both visible and NIR irradiance and under O(2) conditions ranging from anoxia to hyperoxia, explaining its presence in natural niches with similar environmental conditions.
Subject(s)
Biofilms/growth & development , Chlorophyll/metabolism , Cyanobacteria/physiology , Photosynthesis/radiation effects , Cells, Immobilized , Cyanobacteria/growth & development , Cyanobacteria/metabolism , Cyanobacteria/radiation effects , Infrared Rays , Oxygen/metabolism , Oxygen/pharmacology , Photosynthesis/physiologyABSTRACT
BACKGROUND: Traditionally average values of the whole population are considered when analysing microbial cell cultivations. However, a typical microbial population in a bioreactor is heterogeneous in most phenotypes measurable at a single-cell level. There are indications that such heterogeneity may be unfavourable on the one hand (reduces yields and productivities), but also beneficial on the other hand (facilitates quick adaptation to new conditions--i.e. increases the robustness of the fermentation process). Understanding and control of microbial population heterogeneity is thus of major importance for improving microbial cell factory processes. RESULTS: In this work, a dual reporter system was developed and applied to map growth and cell fitness heterogeneities within budding yeast populations during aerobic cultivation in well-mixed bioreactors. The reporter strain, which was based on the expression of green fluorescent protein (GFP) under the control of the ribosomal protein RPL22a promoter, made it possible to distinguish cell growth phases by the level of fluorescence intensity. Furthermore, by exploiting the strong correlation of intracellular GFP level and cell membrane integrity it was possible to distinguish subpopulations with high and low cell membrane robustness and hence ability to withstand freeze-thaw stress. A strong inverse correlation between growth and cell membrane robustness was observed, which further supports the hypothesis that cellular resources are limited and need to be distributed as a trade-off between two functions: growth and robustness. In addition, the trade-off was shown to vary within the population, and the occurrence of two distinct subpopulations shifting between these two antagonistic modes of cell operation could be distinguished. CONCLUSIONS: The reporter strain enabled mapping of population heterogeneities in growth and cell membrane robustness towards freeze-thaw stress at different phases of cell cultivation. The described reporter system is a valuable tool for understanding the effect of environmental conditions on population heterogeneity of microbial cells and thereby to understand cell responses during industrial process-like conditions. It may be applied to identify more robust subpopulations, and for developing novel strategies for strain improvement and process design for more effective bioprocessing.
Subject(s)
Saccharomyces cerevisiae/physiology , Cell Membrane/genetics , Cell Membrane/metabolism , Fermentation , Genes, Reporter , Green Fluorescent Proteins/genetics , Green Fluorescent Proteins/metabolism , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/growth & development , Stress, PhysiologicalABSTRACT
Acetate as the major by-product in industrial-scale bioprocesses with Escherichia coli is found to decrease process efficiency as well as to be toxic to cells, which has several effects like a significant induction of cellular stress responses. However, the underlying phenomena are poorly explored. Therefore, we studied time-resolved population heterogeneity of the E. coli growth reporter strain MG1655/pGS20PrrnBGFPAAV expressing destabilized green fluorescent protein during batch growth on acetate and glucose as sole carbon sources. Additionally, we applied five fluorescent stains targeting different cellular properties (viability as well as metabolic and respiratory activity). Quantitative analysis of flow cytometry data verified that bacterial populations in the bioreactor are more heterogeneous in growth as well as stronger metabolically challenged during growth on acetate as sole carbon source, compared to growth on glucose or acetate after diauxic shift. Interestingly, with acetate as sole carbon source, significant subpopulations were found with some cells that seem to be more robust than the rest of the population. In conclusion, following batch cultures population heterogeneity was evident in all measured parameters. Our approach enabled a deeper study of heterogeneity during growth on the favored substrate glucose as well as on the toxic by-product acetate. Using a combination of activity fluorescent dyes proved to be an accurate and fast alternative as well as a supplement to the use of a reporter strain. However, the choice of combination of stains should be well considered depending on which population traits to aim for.
Subject(s)
Acetates/metabolism , Escherichia coli/growth & development , Escherichia coli/metabolism , Aerobiosis , Batch Cell Culture Techniques , Bioreactors/microbiology , Escherichia coli/genetics , Glucose/metabolism , Green Fluorescent Proteins/genetics , Green Fluorescent Proteins/metabolismABSTRACT
Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.